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A new Wavelet based Edge detection Technique for Iris Imagery

机译:一种基于小波的虹膜图像边缘检测新技术

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In this paper, we present a novel design of a wavelet based edge detection technique. Edge detection is an important task in image processing. Edges in images can be mathematically defined as local singularities. Until recently, the Fourier transforms was the main mathematical tool for analyzing singularities. However, the Fourier transform is global and not well adapted to local singularities. It is hard to find the location and spatial distribution of singularities with Fourier transforms. Wavelet analysis is a local analysis; it is especially suitable for time frequency analysis, which is essential for singularity detection. The fact motivated us to develop a technique using Haar wavelet to find an edge from an image. The proposed technique has been demonstrated for iris imagery and the reported results have been compared with Daubechies D4 wavelet based edge detection technique.
机译:在本文中,我们提出了一种基于小波的边缘检测技术的新颖设计。边缘检测是图像处理中的重要任务。图像中的边缘可以在数学上定义为局部奇异点。直到最近,傅立叶变换还是用于分析奇点的主要数学工具。但是,傅立叶变换是全局的,不能很好地适应局部奇点。用傅立叶变换很难找到奇点的位置和空间分布。小波分析是局部分析;它特别适用于时频分析,这对于奇异性检测必不可少。这一事实促使我们开发一种使用Haar小波从图像中找到边缘的技术。已经证明了所提出的技术用于虹膜图像,并将所报告的结果与基于Daubechies D4小波的边缘检测技术进行了比较。

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